1. Creating data sets. Sampling methods.
2. Sample size.
3. Variable types, their values, missing values.
4. Particular variables analysis. Frequency distribution. Estimations. Testing about proportions.
5. Association between variables.
6. Log-linear models.
7. Comparing two or more populations.
8. Logistic regression.
2. Sample size.
3. Variable types, their values, missing values.
4. Particular variables analysis. Frequency distribution. Estimations. Testing about proportions.
5. Association between variables.
6. Log-linear models.
7. Comparing two or more populations.
8. Logistic regression.